class_docstr: A stream that generates the entire history of a stream at each time step.
  
  Parameters
  ----------
  min_periods : int, default 1
      The number of periods to wait before producing values from the aggregation
      function.
docstr: Computes an aggregation of a stream's history.
  
  Parameters
  ----------
  func : `Callable[[List[float]], float]`
      A aggregation function.
  
  Returns
  -------
  `Stream[float]`
      A stream producing aggregations of the stream history at each time
      step.
docstr_tok: ["Computes","an","aggregation","of","a","stream","'s","history",".","Parameters","--","--","--","--","--","func",":","`","Callable","[","[","List","[","float","]","]",",","float","]","`","A","aggregation","function",".","Returns","--","--","--","-","`","Stream","[","float","]","`","A","stream","producing","aggregations","of","the","stream","history","at","each","time","step","."]
code: def agg(
      self, func: Callable[[List[float]], float]
  ) -> "Stream[float]":
      """Computes an aggregation of a stream's history.
  
      Parameters
      ----------
      func : `Callable[[List[float]], float]`
          A aggregation function.
  
      Returns
      -------
      `Stream[float]`
          A stream producing aggregations of the stream history at each time
          step.
      """
      return ExpandingNode(func)(self).astype("float")
  
imports: from typing import Callable, List
  import numpy
  from tensortrade.feed.core.base import Stream
  from tensortrade.feed.api.float import Float
label_desc: Use image node_id 4 for calling the Expanding obj's underlying member method code with example usage: obj.agg(func) and returns: ExpandingNode